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Application of coarse-grained water model in the study of mixed collectors compounding mechanism in low-rank coal flotation.

Authors :
Wang, Penghui
Liu, Wenli
Zhuo, Qiming
Sun, Xiaopeng
Source :
International Journal of Coal Preparation & Utilization. 2024, Vol. 44 Issue 6, p646-664. 19p.
Publication Year :
2024

Abstract

The investigation of the compounding mechanisms of mixed collectors in low-rank coal flotation has gradually progressed from a macro to a micro level, and the accuracy of research outcomes significantly depends on the development of micro models. While All-Atom Molecular Dynamics (AAMD) simulations have been used for this purpose, the employment of an excessive amount of collector in the system leads to a failure in replicating the actual flotation process, which in turn, limits the practical applicability of research findings. To overcome this drawback, this paper suggests using the MARTINI Coarse-Grained force field (CGFF), developed by the S.J.Marrink group, to construct a simulation system that accurately mimics the amount of collector employed in practical flotation processes. In light of this, to make the MARTINI force field more applicable for research in the low-rank coal field, we employ density functional theory (DFT) and coarse-grained molecular dynamics (CGMD) methods to investigate water cluster interactions, identify magic number clusters, and fit the corresponding CGFF parameters to develop a CG water model suitable for exploring the compounding mechanism of mixed collectors. This research lays the groundwork for future investigations into the aggregation behavior of mixed collectors under actual usage conditions, as well as their synergistic adsorption at the coal/water interface. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19392699
Volume :
44
Issue :
6
Database :
Academic Search Index
Journal :
International Journal of Coal Preparation & Utilization
Publication Type :
Academic Journal
Accession number :
177338162
Full Text :
https://doi.org/10.1080/19392699.2023.2213645